Abstract: Aiming at the control problem of nonlinear dynamic system, a control signal solving model and algorithm based on Process Neural Network (PNN) was proposed. First, a system forward identification model based on PNN was set up by using nonlinear transform mechanism and self-adaptive learning ability of PNN to timcvarying input output signals of dynamic system, then according to the established model, the system control structure and the expected output signals, a control signal solving model and algorithm which satisfies system dynamic signal transform mechanism and transfer constraint relation was constructed. The information processing mechanism based on PNN control model was analyzed and the control signal optimize method based on GA coupled with LMS was given The experiment results veri-fy the feasibility of the model and algorithm.

Key words: Dynamic system, Process control, Process neural network, Solving algorithm, Applications